class_docstr: EfficientNet model.
code: def forward(self, x):
      for module in self.children():
          x = module(x)
      return x
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, drop_connect, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, SE
  from torch.nn import Dropout, Module
label_desc: Use image node_id 3 for calling the EffNet obj's underlying member method code with example usage: obj.forward(x) and returns: x